一种基于全球剖分网格的多源遥感数据空间关联方法

A method of spatial association for multi-sources remote sensing data based on global subdivision grid

针对遥感数据具有多源化且数据量大等特征,同时缺乏统一的空间组织框架,对于数据间空间关联关系建立存在困难等问题,文章提出了基于全球剖分网格的多源遥感数据空间关联模型解决方法:首先采用GeoSOT剖分框架对多源遥感数据进行统一组织与管理,然后根据提出的"网格-数据块-数据"的三层组织概念模型,建立基于全球剖分网格的多源遥感数据空间关联模型;最后进行关联影像的表达实验。实验结果表明,该方法在一定程度上实现了多源遥感数据的结构化组织,有效建立了多源遥感数据的空间关联,并与传统的坐标系统建立对比分析,提高了数据利用的应用效能,整体上促进了遥感数据的使用效率。

For the characteristic of multi-sources and large volume of the remote sensing images, which lack of unified spatial organizational framework, it is difficult to establish the spatial association a- mong remote sensing data. This paper presented a solution based on the global subdivision grid. GeoSOT subdivision framework was used to organize and manage multi-source spatial information in a unified man- ner, and Grid-Block-Data three-layer mechanism was put forward. Based on this mechanism, multi-source remote sensing data spatial association model was designed to support association among remote sensing data. In order to validate this model, multi-source remote sensing image expression experiment was carried out. The experiment result proved the effectiveness of this model, which would improve the application performance of massive multi-source remote sensing data compared to the conventional coordinate system.